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Combining Z-Score and Maternal Copy Number Variation Analysis Increases the Positive Rate and Accuracy in Non-Invasive Prenatal Testing
Objective: To evaluate positive rate and accuracy of non-invasive prenatal testing (NIPT) combining Z-score and maternal copy number variation (CNV) analysis. To assess the relationship between Z-score and positive predictive value (PPV). Methods: This prospective study included 61525 pregnancies to...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9201951/ https://www.ncbi.nlm.nih.gov/pubmed/35719402 http://dx.doi.org/10.3389/fgene.2022.887176 |
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author | Chen, Liheng Wang, Lihong Hu, Zhipeng Tao, Yilun Song, Wenxia An, Yu Li, Xiaoze |
author_facet | Chen, Liheng Wang, Lihong Hu, Zhipeng Tao, Yilun Song, Wenxia An, Yu Li, Xiaoze |
author_sort | Chen, Liheng |
collection | PubMed |
description | Objective: To evaluate positive rate and accuracy of non-invasive prenatal testing (NIPT) combining Z-score and maternal copy number variation (CNV) analysis. To assess the relationship between Z-score and positive predictive value (PPV). Methods: This prospective study included 61525 pregnancies to determine the correlation between Z-scores and PPV in NIPT, and 3184 pregnancies to perform maternal CNVs analysis. Positive results of NIPT were verified by prenatal diagnosis and/or following-up after birth. Z-score grouping, logistic regression analysis, receiver operating characteristic (ROC) curves, and S-curve trends were applied to correlation analysis of Z-scores and PPV. The maternal CNVs were classified according to the technical standard for the interpretation of ACMG. Through genetic counseling, fetal and maternal phenotypes and family histories were collected. Results: Of the 3184 pregnant women, 22 pregnancies were positive for outlier Z-scores, suggesting fetal aneuploidy. 12 out of 22 pregnancies were true positive (PPV = 54.5%). 17 pregnancies were found maternal pathogenic or likely pathogenic CNVs (> 0.5 Mb) through maternal CNV analysis. Prenatal diagnosis revealed that 7 out of 11 fetuses carried the same CNVs as the mother. Considering the abnormal biochemical indicators during pregnancy and CNV-related clinical phenotypes after birth, two male fetuses without prenatal diagnosis were suspected to carry the maternally-derived CNVs. Further, we identified three CNV-related family histories with variable phenotypes. Statistical analysis of the 61525 pregnancies revealed that Z-scores of chromosomes 21 and 18 were significantly associated with PPV at 3 ≤ Z ≤ 40. Notably, three pregnancies with Z > 40 were both maternal full aneuploidy. At Z < -3, fetuses carried microdeletions instead of monosomies. Sex chromosome trisomy was significantly higher PPV than monosomy. Conclusion: The positive rate of the NIPT screening model combining Z-score and maternal CNV analysis increased from 6.91‰ (22/3184) to 12.25‰ (39/3184) and true positives increased from 12 to 21 pregnancies. We found that this method could improve the positive rate and accuracy of NIPT for aneuploidies and CNVs without increasing testing costs. It provides an early warning for the inheritance of pathogenic CNVs to the next generation. |
format | Online Article Text |
id | pubmed-9201951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92019512022-06-17 Combining Z-Score and Maternal Copy Number Variation Analysis Increases the Positive Rate and Accuracy in Non-Invasive Prenatal Testing Chen, Liheng Wang, Lihong Hu, Zhipeng Tao, Yilun Song, Wenxia An, Yu Li, Xiaoze Front Genet Genetics Objective: To evaluate positive rate and accuracy of non-invasive prenatal testing (NIPT) combining Z-score and maternal copy number variation (CNV) analysis. To assess the relationship between Z-score and positive predictive value (PPV). Methods: This prospective study included 61525 pregnancies to determine the correlation between Z-scores and PPV in NIPT, and 3184 pregnancies to perform maternal CNVs analysis. Positive results of NIPT were verified by prenatal diagnosis and/or following-up after birth. Z-score grouping, logistic regression analysis, receiver operating characteristic (ROC) curves, and S-curve trends were applied to correlation analysis of Z-scores and PPV. The maternal CNVs were classified according to the technical standard for the interpretation of ACMG. Through genetic counseling, fetal and maternal phenotypes and family histories were collected. Results: Of the 3184 pregnant women, 22 pregnancies were positive for outlier Z-scores, suggesting fetal aneuploidy. 12 out of 22 pregnancies were true positive (PPV = 54.5%). 17 pregnancies were found maternal pathogenic or likely pathogenic CNVs (> 0.5 Mb) through maternal CNV analysis. Prenatal diagnosis revealed that 7 out of 11 fetuses carried the same CNVs as the mother. Considering the abnormal biochemical indicators during pregnancy and CNV-related clinical phenotypes after birth, two male fetuses without prenatal diagnosis were suspected to carry the maternally-derived CNVs. Further, we identified three CNV-related family histories with variable phenotypes. Statistical analysis of the 61525 pregnancies revealed that Z-scores of chromosomes 21 and 18 were significantly associated with PPV at 3 ≤ Z ≤ 40. Notably, three pregnancies with Z > 40 were both maternal full aneuploidy. At Z < -3, fetuses carried microdeletions instead of monosomies. Sex chromosome trisomy was significantly higher PPV than monosomy. Conclusion: The positive rate of the NIPT screening model combining Z-score and maternal CNV analysis increased from 6.91‰ (22/3184) to 12.25‰ (39/3184) and true positives increased from 12 to 21 pregnancies. We found that this method could improve the positive rate and accuracy of NIPT for aneuploidies and CNVs without increasing testing costs. It provides an early warning for the inheritance of pathogenic CNVs to the next generation. Frontiers Media S.A. 2022-06-02 /pmc/articles/PMC9201951/ /pubmed/35719402 http://dx.doi.org/10.3389/fgene.2022.887176 Text en Copyright © 2022 Chen, Wang, Hu, Tao, Song, An and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Chen, Liheng Wang, Lihong Hu, Zhipeng Tao, Yilun Song, Wenxia An, Yu Li, Xiaoze Combining Z-Score and Maternal Copy Number Variation Analysis Increases the Positive Rate and Accuracy in Non-Invasive Prenatal Testing |
title | Combining Z-Score and Maternal Copy Number Variation Analysis Increases the Positive Rate and Accuracy in Non-Invasive Prenatal Testing |
title_full | Combining Z-Score and Maternal Copy Number Variation Analysis Increases the Positive Rate and Accuracy in Non-Invasive Prenatal Testing |
title_fullStr | Combining Z-Score and Maternal Copy Number Variation Analysis Increases the Positive Rate and Accuracy in Non-Invasive Prenatal Testing |
title_full_unstemmed | Combining Z-Score and Maternal Copy Number Variation Analysis Increases the Positive Rate and Accuracy in Non-Invasive Prenatal Testing |
title_short | Combining Z-Score and Maternal Copy Number Variation Analysis Increases the Positive Rate and Accuracy in Non-Invasive Prenatal Testing |
title_sort | combining z-score and maternal copy number variation analysis increases the positive rate and accuracy in non-invasive prenatal testing |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9201951/ https://www.ncbi.nlm.nih.gov/pubmed/35719402 http://dx.doi.org/10.3389/fgene.2022.887176 |
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